The Pixon algorithm used for the reconstruction of images from RHESSI data is an adaptation of the program successfully used to analyze data from Yohkoh/HXT (Metcalf et al. 1996). Unlike Clean, which models the source as a collection of point sources, this algorithm seeks a superposition of circular sources or pixons of different sizes and parabolic profiles that best reproduces the measured modulations from the different detectors. The goal is to construct the image with the fewest degrees of freedom (the fewest pixons) that is consistent with the observations (i.e., the image predicts the modulated count rates with a value of χ2 per degree of freedom acceptably close to one). This technique is generally thought to provide the most accurate image photometry but at the price of taking well over an hour per 128×128 pixel image even on the fastest available PC. As with the other reconstruction algorithms, the Pixon technique as currently implemented can have difficulties with the most compact sources breaking up when the finest grids are used. This problem can be alleviated with various user-controlled parameters.

This page last updated: June 27, 2011